The insights section is here to give you precise information and analytics on
individual products and visitors. TasteHit monitors the performance of products
(visits, clicks, add-to-carts) and finds relationships between products in the
catalog (what is visited before/after, what is often bought together) and
relationships between products and individual visitors.

In this section we describe the 3 sections which appear in the TasteHit
dashboard:

The products insights page contains a table showing information on products and
the way these products are being discovered by visitors.

In this table products are sorted by "highest change in visits" week-to-week, in
other words: the first products shown are the ones that had the biggest increase
in popularity over last the last two weeks.

If you want to find a specific product, you can use the search menu which can
filter items by specific fields/keywords.

Popularity rank represents the popularity of the product measured by the
number of visits. The most popular product will have rank 1, the second most
popular will have a rank of 2, and so on.

Product views is the actual number of times this product was viewed over
the last months.

Change in visits is the number by which the number of visits of this
product was increased or decreased over the last week compared to the previous
week.

Typical recommendations are the products that TasteHit would present to a
visitor if the recommendations
algorithm is configured and
if the visitor has not seen anything else before and lands on this product for
the first time.

Timestamp is the date/time at which the statistics for these product were
calculated.

If you click on the '+' sign in front of the product, a detailed view will
open under the product and will look like this:

This detailed view contains more information on the specific product you are
looking at:

Visited before: the 5 products which were visited the most before the
current product.

Visited after: the 5 products which were visited the most after the
current product.

Added to cart after: the 5 products which were added to cart the most
after this product was visited.

Bought together: 5 products which are often found in the same cart with
the current product.

Most effective recs: 5 most effective recommendations on the current
product's product page. "Most effective products" means: the recommendations
which led to the highest number of cart additions.

Most displayed recs: 5 most displayed recommendations on the current
product's product page.

You can monitor the behavior that led to a buying behavior for individual
visitors.

This helps you understand how visitors browse your shop, monitor typical buying
behaviors and see how recommendations help the visitor discover new products.

The menu allows you to pick conversions in a range between certain days.

If you click on the '+' sign in front one product to display the complete
journey of the consumer:

To help you better understand what conversions mean, different types were
defined, which correspond to the checkboxes you see on the right of the screen:

Flexible: A specific user has clicked on a specific item inside a
recommendation and has added this same item to his shopping cart. The order of
actions is not taken into account.

Ordered: Same as Flexible, but the "click on recommendation" has to come
before the "add-to-cart".

In a day: Same as Ordered. In addition the two actions have to be done in
the same 24 hours. For example, if a user on a recommendation of item A on
Monday at 9am, and only adds item A to his cart Tuesday at 10am, when he comes
back to your site, the conversion will not be counted as a "In a day"
recommendation.

Direct: Same as In a day. In addition the two actions have to be
consecutive. For example, if a user clicks on a recommendation of item A, visits
the product page of item A, then visits item B, then adds item A to cart, the
conversion will not be counted as a "Direct" recommendation.

This sections shows you content similar to the Product
insights section, but in an aggregated way. All product
information is aggregated by product parameter. These product parameters come
from the product feed you configured.

The goal of these graphs is to get a high-level understanding of the popularity
and efficiency of different product categories.